EY
Databricks Data Engineer - Manager - Consulting - Miami
EY, Woodbridge, New Jersey, United States
Databricks Data Engineer - Manager - Consulting - Miami
Location: Anywhere in Country
At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.
We’ll empower you to build a better working world.
Technology – Data and Decision Science – Data Engineering – Manager
We are looking for a dynamic and experienced Manager of Data Engineering to lead our team in designing and implementing complex cloud analytics solutions with a strong focus on Databricks. The ideal candidate will possess deep technical expertise in data architecture, cloud technologies, and analytics, along with exceptional leadership and client management skills.
In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions.
Key Responsibilities
Understanding and analyzing business requirements to translate them into technical requirements.
Designing, building, and operating scalable data architecture and modeling solutions.
Staying up to date with the latest trends and emerging technologies to maintain a competitive edge.
Leading workstream delivery and ensuring quality in all processes.
Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services.
Implementing resource plans and budgets while managing engagement economics.
Skills and Attributes for Success
Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (AWS, Azure, GCP).
Oversee the architecture of complex cloud analytics solutions, ensuring alignment with business objectives and best practices.
Manage and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement.
Collaborate with clients to understand their analytics needs and deliver tailored solutions that drive business value.
Ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance.
Drive end‑to‑end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services.
Communicate effectively with stakeholders, including technical and non‑technical audiences, to convey complex data concepts and project progress.
Manage client relationships and expectations, ensuring high levels of satisfaction and engagement.
Stay abreast of the latest trends and technologies in data engineering, cloud computing, and analytics.
Strong analytical and problem‑solving abilities.
Excellent communication skills, with the ability to convey complex information clearly.
Proven experience in managing and delivering projects effectively.
Ability to build and manage relationships with clients and stakeholders.
Qualifications
Bachelor’s degree in computer science, engineering, or a related field (Master’s preferred).
Typically no less than 4–6 years of relevant experience in data engineering, focusing on cloud data solutions and analytics.
Proven expertise in Databricks and experience with Spark for big‑data processing.
Strong background in data architecture and design, experience building complex cloud analytics solutions.
Experience in leading and managing teams, mentoring and developing talent.
Strong programming skills in Python, Scala, or SQL.
Excellent problem‑solving skills and ability to work independently and as part of a team.
Strong communication and interpersonal skills, with a focus on client management.
Required Expertise for Managerial Role
Strategic Leadership: Align data engineering initiatives with organizational goals and drive strategic vision.
Project Management: Manage multiple projects and teams, ensuring timely delivery and adherence to project scope.
Stakeholder Engagement: Engage with executives to understand needs and present effective solutions.
Change Management: Guide clients through data transformation and technology adoption.
Risk Management: Identify potential risks and develop mitigation strategies.
Technical Leadership: Lead technical discussions and make architectural decisions.
Documentation and Reporting: Create comprehensive documentation and reports to communicate progress and outcomes.
Large‑Scale Implementation Programs
Enterprise Data Lake Implementation: Led the design and deployment of a cloud‑based data lake for a Fortune 500 retail client, integrating multiple data sources.
Real‑Time Analytics Platform: Managed the development of a real‑time analytics platform enabling fraud detection for a financial services organization.
Data Warehouse Modernization: Oversaw modernization of a legacy data warehouse to a cloud‑native architecture for a healthcare provider.
Ideally, you’ll also have
Experience with advanced data analytics tools and techniques.
Familiarity with machine learning concepts and applications.
Knowledge of industry trends and best practices in data engineering.
Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
Knowledge of data governance and compliance standards.
Experience with machine learning frameworks and tools.
What We Look For We seek individuals who are not only technically proficient but also possess the qualities of top performers: strong collaboration, adaptability, continuous learning, passion for results, and a desire to make a meaningful impact.
Benefits & Compensation
Comprehensive compensation and benefits package with base salary ranging from $125,500 to $230,200 in the U.S., with higher ranges for major metro areas.
Medical and dental coverage, pension and 401(k) plans, and paid time off.
Hybrid work model with 40‑60% in‑person collaboration for client‑serving roles.
Flexible vacation policy with choice of time off based on personal circumstances and EY holidays.
Application Are you ready to shape your future with confidence? Apply today.
EY accepts applications for this position on an ongoing basis.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records. EY is committed to providing reasonable accommodation to qualified individuals with disabilities. If you need assistance applying online or requesting an accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate related inquiries, then Option 1 for candidate queries and finally Option 2 for candidates with an inquiry, which will route you to EY’s Talent Shared Services Team or email the TSS at ssc.customersupport@ey.com.
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At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.
We’ll empower you to build a better working world.
Technology – Data and Decision Science – Data Engineering – Manager
We are looking for a dynamic and experienced Manager of Data Engineering to lead our team in designing and implementing complex cloud analytics solutions with a strong focus on Databricks. The ideal candidate will possess deep technical expertise in data architecture, cloud technologies, and analytics, along with exceptional leadership and client management skills.
In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions.
Key Responsibilities
Understanding and analyzing business requirements to translate them into technical requirements.
Designing, building, and operating scalable data architecture and modeling solutions.
Staying up to date with the latest trends and emerging technologies to maintain a competitive edge.
Leading workstream delivery and ensuring quality in all processes.
Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services.
Implementing resource plans and budgets while managing engagement economics.
Skills and Attributes for Success
Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (AWS, Azure, GCP).
Oversee the architecture of complex cloud analytics solutions, ensuring alignment with business objectives and best practices.
Manage and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement.
Collaborate with clients to understand their analytics needs and deliver tailored solutions that drive business value.
Ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance.
Drive end‑to‑end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services.
Communicate effectively with stakeholders, including technical and non‑technical audiences, to convey complex data concepts and project progress.
Manage client relationships and expectations, ensuring high levels of satisfaction and engagement.
Stay abreast of the latest trends and technologies in data engineering, cloud computing, and analytics.
Strong analytical and problem‑solving abilities.
Excellent communication skills, with the ability to convey complex information clearly.
Proven experience in managing and delivering projects effectively.
Ability to build and manage relationships with clients and stakeholders.
Qualifications
Bachelor’s degree in computer science, engineering, or a related field (Master’s preferred).
Typically no less than 4–6 years of relevant experience in data engineering, focusing on cloud data solutions and analytics.
Proven expertise in Databricks and experience with Spark for big‑data processing.
Strong background in data architecture and design, experience building complex cloud analytics solutions.
Experience in leading and managing teams, mentoring and developing talent.
Strong programming skills in Python, Scala, or SQL.
Excellent problem‑solving skills and ability to work independently and as part of a team.
Strong communication and interpersonal skills, with a focus on client management.
Required Expertise for Managerial Role
Strategic Leadership: Align data engineering initiatives with organizational goals and drive strategic vision.
Project Management: Manage multiple projects and teams, ensuring timely delivery and adherence to project scope.
Stakeholder Engagement: Engage with executives to understand needs and present effective solutions.
Change Management: Guide clients through data transformation and technology adoption.
Risk Management: Identify potential risks and develop mitigation strategies.
Technical Leadership: Lead technical discussions and make architectural decisions.
Documentation and Reporting: Create comprehensive documentation and reports to communicate progress and outcomes.
Large‑Scale Implementation Programs
Enterprise Data Lake Implementation: Led the design and deployment of a cloud‑based data lake for a Fortune 500 retail client, integrating multiple data sources.
Real‑Time Analytics Platform: Managed the development of a real‑time analytics platform enabling fraud detection for a financial services organization.
Data Warehouse Modernization: Oversaw modernization of a legacy data warehouse to a cloud‑native architecture for a healthcare provider.
Ideally, you’ll also have
Experience with advanced data analytics tools and techniques.
Familiarity with machine learning concepts and applications.
Knowledge of industry trends and best practices in data engineering.
Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
Knowledge of data governance and compliance standards.
Experience with machine learning frameworks and tools.
What We Look For We seek individuals who are not only technically proficient but also possess the qualities of top performers: strong collaboration, adaptability, continuous learning, passion for results, and a desire to make a meaningful impact.
Benefits & Compensation
Comprehensive compensation and benefits package with base salary ranging from $125,500 to $230,200 in the U.S., with higher ranges for major metro areas.
Medical and dental coverage, pension and 401(k) plans, and paid time off.
Hybrid work model with 40‑60% in‑person collaboration for client‑serving roles.
Flexible vacation policy with choice of time off based on personal circumstances and EY holidays.
Application Are you ready to shape your future with confidence? Apply today.
EY accepts applications for this position on an ongoing basis.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records. EY is committed to providing reasonable accommodation to qualified individuals with disabilities. If you need assistance applying online or requesting an accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate related inquiries, then Option 1 for candidate queries and finally Option 2 for candidates with an inquiry, which will route you to EY’s Talent Shared Services Team or email the TSS at ssc.customersupport@ey.com.
#J-18808-Ljbffr